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  <div class="section" id="numpy-bincount">
<h1>numpy.bincount<a class="headerlink" href="#numpy-bincount" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="numpy.bincount">
<code class="sig-prename descclassname">numpy.</code><code class="sig-name descname">bincount</code><span class="sig-paren">(</span><em class="sig-param">x</em>, <em class="sig-param">weights=None</em>, <em class="sig-param">minlength=0</em><span class="sig-paren">)</span><a class="headerlink" href="#numpy.bincount" title="Permalink to this definition">¶</a></dt>
<dd><p>Count number of occurrences of each value in array of non-negative ints.</p>
<p>The number of bins (of size 1) is one larger than the largest value in
<em class="xref py py-obj">x</em>. If <em class="xref py py-obj">minlength</em> is specified, there will be at least this number
of bins in the output array (though it will be longer if necessary,
depending on the contents of <em class="xref py py-obj">x</em>).
Each bin gives the number of occurrences of its index value in <em class="xref py py-obj">x</em>.
If <em class="xref py py-obj">weights</em> is specified the input array is weighted by it, i.e. if a
value <code class="docutils literal notranslate"><span class="pre">n</span></code> is found at position <code class="docutils literal notranslate"><span class="pre">i</span></code>, <code class="docutils literal notranslate"><span class="pre">out[n]</span> <span class="pre">+=</span> <span class="pre">weight[i]</span></code> instead
of <code class="docutils literal notranslate"><span class="pre">out[n]</span> <span class="pre">+=</span> <span class="pre">1</span></code>.</p>
<dl class="field-list">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><dl>
<dt><strong>x</strong><span class="classifier">array_like, 1 dimension, nonnegative ints</span></dt><dd><p>Input array.</p>
</dd>
<dt><strong>weights</strong><span class="classifier">array_like, optional</span></dt><dd><p>Weights, array of the same shape as <em class="xref py py-obj">x</em>.</p>
</dd>
<dt><strong>minlength</strong><span class="classifier">int, optional</span></dt><dd><p>A minimum number of bins for the output array.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 1.6.0.</span></p>
</div>
</dd>
</dl>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><dl class="simple">
<dt><strong>out</strong><span class="classifier">ndarray of ints</span></dt><dd><p>The result of binning the input array.
The length of <em class="xref py py-obj">out</em> is equal to <code class="docutils literal notranslate"><span class="pre">np.amax(x)+1</span></code>.</p>
</dd>
</dl>
</dd>
<dt class="field-odd">Raises</dt>
<dd class="field-odd"><dl class="simple">
<dt><strong>ValueError</strong></dt><dd><p>If the input is not 1-dimensional, or contains elements with negative
values, or if <em class="xref py py-obj">minlength</em> is negative.</p>
</dd>
<dt><strong>TypeError</strong></dt><dd><p>If the type of the input is float or complex.</p>
</dd>
</dl>
</dd>
</dl>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<p><a class="reference internal" href="numpy.histogram.html#numpy.histogram" title="numpy.histogram"><code class="xref py py-obj docutils literal notranslate"><span class="pre">histogram</span></code></a>, <a class="reference internal" href="numpy.digitize.html#numpy.digitize" title="numpy.digitize"><code class="xref py py-obj docutils literal notranslate"><span class="pre">digitize</span></code></a>, <a class="reference internal" href="numpy.unique.html#numpy.unique" title="numpy.unique"><code class="xref py py-obj docutils literal notranslate"><span class="pre">unique</span></code></a></p>
</div>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">bincount</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">5</span><span class="p">))</span>
<span class="go">array([1, 1, 1, 1, 1])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">bincount</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">7</span><span class="p">]))</span>
<span class="go">array([1, 3, 1, 1, 0, 0, 0, 1])</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">7</span><span class="p">,</span> <span class="mi">23</span><span class="p">])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">bincount</span><span class="p">(</span><span class="n">x</span><span class="p">)</span><span class="o">.</span><span class="n">size</span> <span class="o">==</span> <span class="n">np</span><span class="o">.</span><span class="n">amax</span><span class="p">(</span><span class="n">x</span><span class="p">)</span><span class="o">+</span><span class="mi">1</span>
<span class="go">True</span>
</pre></div>
</div>
<p>The input array needs to be of integer dtype, otherwise a
TypeError is raised:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">bincount</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">5</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">float</span><span class="p">))</span>
<span class="gt">Traceback (most recent call last):</span>
  File <span class="nb">&quot;&lt;stdin&gt;&quot;</span>, line <span class="m">1</span>, in <span class="n">&lt;module&gt;</span>
<span class="gr">TypeError</span>: <span class="n">array cannot be safely cast to required type</span>
</pre></div>
</div>
<p>A possible use of <code class="docutils literal notranslate"><span class="pre">bincount</span></code> is to perform sums over
variable-size chunks of an array, using the <code class="docutils literal notranslate"><span class="pre">weights</span></code> keyword.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">w</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mf">0.3</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.2</span><span class="p">,</span> <span class="mf">0.7</span><span class="p">,</span> <span class="mf">1.</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.6</span><span class="p">])</span> <span class="c1"># weights</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">bincount</span><span class="p">(</span><span class="n">x</span><span class="p">,</span>  <span class="n">weights</span><span class="o">=</span><span class="n">w</span><span class="p">)</span>
<span class="go">array([ 0.3,  0.7,  1.1])</span>
</pre></div>
</div>
</dd></dl>

</div>


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